Rotating machines are the backbone of the present industrial world. Early fault detection and conditioning of these machines are primary concern of the researchers associated in this field. There are various faults (assembly error, coupling misalignment, looseness, imbalance, rotor crack, etc.) that cause malfunction of rotating machinery. Imbalance is one of the oldest problem and still challenging to perfectly balance the rotor. Imbalance leads to another inherent fault, i.e., coupling misalignment, especially in dual rotor or rotor trainsystem. Imbalance and misalignment cause excessive vibration in the system that tends to shatter failure of the critical components of rotating machinery. In this article, active magnetic bearings (AMBs) are utilized to suppress the excessive vibration generated due to imbalance and misalignment. To regulate the controllingcurrent of AMB a proportional integral derivative (PID) feedback controller is employed. A quantification technique is suggested to evaluate the tuned AMB characteristics along with imbalance and coupling misalignment dynamic parameters. A finite element method (FEM) modelling with high-frequency reduction scheme is utilized to acquire reduced system equations of motion. There are two advantages of employing condensation scheme, first, it reduces the number of sensors required and second, only linear (practicallymeasurable) degrees of freedom are present in equations of motion derived. A SIMULINK^TM code is prepared to solve a reduced linear differential equation. The time series feedback signals (current and displacement)obtained are transformed into a frequency series utilizing Fast Fourier Transformation (FFT) and utilized in developed algorithm. To establish the accuracy and effectiveness of the methodology, the estimated parametersare evaluated under two different frequency bands against measurement and modelling error (5% variation in mass of the disc and bearing characteristic parameters).